Hey, Google, Is it What the Holocaust Really Looked Like? Auditing Biases in Visual Representation of the Holocaust on Web Search Engines

Makhortykh, Mykola; Urman, Aleksandra; Ulloa, Roberto (27 May 2021). Hey, Google, Is it What the Holocaust Really Looked Like? Auditing Biases in Visual Representation of the Holocaust on Web Search Engines (Unpublished). In: 71st Annual ICA conference - "Engaging the Essential Work of Care: Communication, Connectedness, and Social Justice". Virtual. 27.05.-31.05.2021.

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The potential for bias in web search engine outputs and its negative effects on the ability of individuals and societies to be adequately informed is increasingly recognized. So far, research focuses on different types of bias in relation to general concepts (e.g., genderor race) or recent events (e.g., political elections). However, search engine outputs related to historical events, in particular highly traumatic ones such as crimes against humanity, can also be biased. Such biases can be viewed as a breach of memory ethics (e.g., the responsibility for properly remembering the victims) and also be used to manipulate the public sphere (e.g., by distorting historical facts for mobilizing the audience). To understand potential biases in algorithmic curation of historical information, we use agent-based testing to conduct algorithmic auditing of image search results related to a notorious case of historical atrocities - the Holocaust - across six search engines in English and Russian. Using quantitative content analysis, we identify different forms of bias related to the representation of the Holocaust (i.e., misattribution, trivialization, revisionism, and over-representation bias) and compare the difference in their prevalence depending on the engine/language selection. Our findings indicate substantial variation in terms of bias visibility between the search engines, and highlight the need for integrating memory ethics into the design of information curation mechanisms dealing with historical events.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	03 Faculty of Business, Economics and Social Sciences > Social Sciences > Institute of Communication and Media Studies (ICMB)
UniBE Contributor:	Makhortykh, Mykola, Urman, Aleksandra
Subjects:	000 Computer science, knowledge & systems 300 Social sciences, sociology & anthropology 900 History
Language:	English
Submitter:	Mykola Makhortykh
Date Deposited:	19 Jul 2021 09:29
Last Modified:	05 Dec 2022 15:51
Uncontrolled Keywords:	Holocaust, bias, history, search engine, algorithms, antisemitism, misattribution
URI:	https://boris.unibe.ch/id/eprint/156708